Robust Economic-Statistical Design of Acceptance Control Chart

Acceptance control charts (ACC), as an effective tool for monitoring highly capable processes, establish control limits based on specification limits when the fluctuation of the process mean is permitted or inevitable. For designing these charts by minimizing economic costs subject to statistical constraints, an economic-statistical model is developed in this paper. However, the parameters of some processes are in practice uncertain. Such uncertainty could be an obstacle to getting the best design. Therefore, the parameters are investigated by a robust optimization approach. For this reason, a solution procedure utilizing a genetic algorithm (GA) is presented. The algorithm procedure is illustrated based on numerical studies. Additionally, sensitivity analysis and some comparisons are carried out for more investigations. The results indicate better performance of the proposed approach in designing ACC and more reliable solutions for practitioners.